{"slug":"tdimino-dag-typesafe","name":"dag-typesafe","description":">-","long_description":"---\nname: dag-typesafe\ndescription: >-\n  Analyze a repository's type system and generate type-safe DAG execution pipelines\n  with GraphSentry-style certificate verification. This skill should be used when\n  building LLM-driven workflows that need deterministic type safety, when composing\n  typed operations into validated execution graphs, or when adding contract-checked\n  pipeline orchestration to any codebase. Supports Python (Pydantic) and TypeScript (Zod).\nargument-hint: \"[analyze|compose|compile|validate|registry] [args...]\"\n---\n\n# dag-typesafe\n\nDeterministic type safety via directed acyclic graphs for reasoning language models.\n\nAnalyze any repo's public API surface, extract a typed node registry, compose validated\nexecution DAGs from natural language, and compile them into native pipeline code with\nGraphSentry-style `(artifact, certificate)` verification at every node boundary.\n\n## Category\n\nCode Scaffolding & Templates\n\n## Core Concepts\n\nThree layers compose into a single architecture:\n\n1. **Typed Node Registry** — the repo's public functions/classes extracted as typed nodes\n   with JSON Schema input/output contracts. The LLM selects from this registry; it never\n   generates arbitrary code.\n\n2. **DAG Plan** — a language-neutral execution graph where nodes reference registry entries\n   and edges are schema-validated. No cycles, all inputs satisfied, all types compatible.\n\n3. **Certificates** — each node emits an `(artifact, certificate)` pair. Certificates are\n   deterministic predicates evaluated from logged evidence. Failed certificates halt the\n   pipeline with diagnostic context. Based on GraphSentry (Li et al., 2026).\n\n## Commands\n\nParse `$ARGUMENTS` to determine which command to run:\n\n### `analyze`\n\nExtract a typed node registry from the current repository.\n\n```bash\npython3 ~/.claude/skills/dag-typesafe/scripts/analyze.py [--language python|typescript|auto] [--output dag-registry.json]\n```\n\n1. Detect repo language(s) from file extensions and config files\n2. Run the appropriate extractor(s) from `extractors/`\n3. Walk the AST for public API surface only (exported functions, public classes, API endpoints)\n4. Convert type annotations to JSON Schema\n5. Output `dag-registry.json` at repo root\n\n### `compose`\n\nGenerate a DAG plan from natural language using the typed registry.\n\nThe compose phase is **endpoint-agnostic** — it works with any OpenAI-compatible API\n(OpenRouter, Groq, Subq Code, local models) or in-session via Claude Code.\n\n**In-session mode (default):** Build a structured prompt from the registry and task\ndescription, then use the current Claude Code session to generate the DAG plan.\n\n**Headless mode:** Set `DAG_LLM_BASE_URL` and `DAG_LLM_API_KEY` environment variables\nto point at any OpenAI-compatible endpoint.\n\n```bash\npython3 ~/.claude/skills/dag-typesafe/scripts/compose.py \"task description\" --registry dag-registry.json [--output dag-plan.json] [--provider session|openai]\n```\n\n1. Load registry from `dag-registry.json`\n2. Build structured prompt constraining LLM to node selection and parameterization\n3. Generate DAG plan conforming to `schemas/dag-plan.schema.json`\n4. Validate the plan (type compatibility, no cycles, all inputs satisfied)\n5. Generate certificate predicates for each node\n6. Output `dag-plan.json`\n\n### `compile`\n\nCompile a validated DAG plan into native executable code.\n\n```bash\npython3 ~/.claude/skills/dag-typesafe/scripts/compile.py dag-plan.json [--target python|typescript] [--output pipeline.py]\n```\n\n1. Read validated `dag-plan.json` and `dag-registry.json`\n2. Topologically sort nodes\n3. Generate native pipeline code via inline code generation\n4. Wrap each node call in schema validation (Pydantic `.model_validate()` / Zod `.parse()`)\n5. Inject certificate predicate evaluation at every node boundary\n6. Output executable pipeline file with zero runtime dependencies beyond standard validation libs\n\n### `validate`\n\nType-check an existing DAG plan against a registry.\n\n```bash\npython3 ~/.claude/skills/dag-typesafe/scripts/validate.py dag-plan.json --registry dag-registry.json\n```\n\nChecks: cycle detection, edge type compatibility, required input satisfaction, certificate\npredicate well-formedness, registry reference integrity.\n\n### `registry`\n\nInspect, filter, and query the typed node registry.\n\n```bash\npython3 ~/.claude/skills/dag-typesafe/scripts/registry.py [--filter \"pattern\"] [--show-schemas] [--stats]\n```\n\n## Schemas\n\nAll schemas live in `schemas/` as JSON Schema (draft 2020-12):\n\n- `dag-plan.schema.json` — DAG plan format (nodes, edges, metadata)\n- `registry.schema.json` — typed node registry format\n- `certificate.schema.json` — GraphSentry certificate format\n\nRead these schemas before generating or validating any DAG artifacts.\n\n## Extractors\n\nLanguage-specific type extractors in `extractors/`:\n\n| Extractor | Source Types | Output |\n|-----------|-------------|--------|\n| `python_extractor.py` | Pydantic BaseModel, dataclass, TypedDict, function annotations | JSON Schema |\n| `typescript_extractor.py` | Zod schemas, interfaces, type aliases, function signatures | JSON Schema |\n\nEach extractor walks the AST, identifies public API surface, and converts type definitions\nto JSON Schema for the registry. Internal/private symbols are excluded.\n\n## Code Generation\n\nThe compiler generates pipeline code inline (no external templates). Both Python and TypeScript\ntargets produce complete executable files with:\n\n- Certificate/CertificateError classes\n- Topologically sorted node execution\n- Per-node certificate emission and predicate evaluation\n- Predicate expression sandboxing (AST-validated safe subset only)\n\n## LLM Provider Configuration\n\nFor headless/CI use, configure via environment variables:\n\n```bash\nexport DAG_LLM_BASE_URL=\"https://openrouter.ai/api/v1\"  # or Groq, Subq, local\nexport DAG_LLM_API_KEY=\"your-key\"\nexport DAG_LLM_MODEL=\"anthropic/claude-sonnet-4-20250514\"  # model identifier\n```\n\nWhen these are unset, compose mode generates a structured prompt for in-session use.\n\n## Research Basis\n\nThis skill synthesizes patterns from:\n\n- **GraphSentry** (Li et al., 2026) — certificate-driven typed DAGs, contract-checked graph surgery\n- **ChopChop** (Nagy et al., POPL 2026) — semantic constrained decoding via coinductive realizability\n- **PlanCompiler** (prnvh, 2026) — LLM confined to typed node registry selection\n- **PlanAI** (Provos, 2026) — Pydantic-typed DAG orchestration with automatic routing\n- **Agint** (Chivukula et al., 2025) — type floors (text→data→spec→code) in agentic graph compilation\n\nFull source list: `references/research-sources.md`\n","tagline":">-","category":"automation","commerce":{"type":"unknown","billing":"unknown","amount":null,"currency":null,"sourceUrl":null,"checkedAt":null,"runtime":"unknown","purchaseUrl":null,"checkout":"external","purchaseRequiresUserConsent":true},"tags":["agent-skill"],"author":"tdimino","verified":false,"attribution":{"status":"registry_indexed","statusLabel":"Registry indexed","shortLabel":"REGISTRY INDEXED","sourceLabel":"recursive skill source sync","sourceDetail":"tdimino/claude-code-minoan","creatorName":"tdimino","creatorUrl":"https://github.com/tdimino","sourceUrl":"https://github.com/tdimino/claude-code-minoan/tree/main/skills/core-development/dag-typesafe","indexedBy":"OpenAgentSkill community index","claimUrl":"https://www.openagentskill.com/skills/tdimino-dag-typesafe#claim-this-skill","claimCta":"Claim this skill","trustNote":"This listing was indexed from public sources and is not marked official until a maintainer claim is approved.","publicNote":"Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals."},"stats":{"stars":41,"forks":4,"verified_installs":0,"successful_runs":0,"total_outcomes":0,"rating":0,"review_count":0,"quality_score":34.46},"quality":{"score":60,"tier":"promising","label":"Promising","summary":"Useful candidate, but compare it with alternatives before adopting.","signals":[{"label":"GitHub stars","value":"41","tone":"neutral"},{"label":"Freshness","value":"1mo ago","tone":"positive"},{"label":"Install ready","value":"Yes","tone":"positive"},{"label":"License","value":"MIT","tone":"neutral"}],"warnings":["Low GitHub adoption signal","No critical security issues identified. The skill only parses ASTs and generates code; it does not execute arbitrary repo code directly."]},"trust":{"version":"trust-score-v5","score":51,"base_score":59,"outcome_confidence":0,"tier":"risk","label":"Do not auto-install","summary":"Trust Score v5 found insufficient evidence for agent installation. 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